Apparatus and method for determining wind profiles and for predicting clear air turbulence

ABSTRACT

A clear air turbulence (CAT) detection system performs a nested grid modeling algorithm to detect CAT along the flight path of an aircraft. The aircraft stores coarse simulation information and utilizes the information to perform large scale weather modeling over a large grid. On board sensors are utilized to generate observational information to model atmospheric conditions within a smaller grid, nested within the larger grid, and including the flight path of the aircraft. A nowcast predicting turbulence along the flight path in the near future alerts the pilot to the likelihood of encountering clear air turbulence. A data link may be utilized to receive coarse simulation data or observational data from sources external to the aircraft. Additionally, the coarse simulation information may include turbulence forecast data and the observational information is used to refine the turbulence forecast to more accurately predict clear air turbulence along the flight path of the aircraft.

CROSS-REFERENCES TO RELATED APPLICATIONS

The application is related to and claims priority from U.S. applicationSer. No. 60/091,859 for “Apparatus and Method for Determining WindProfiles and for Predicting Clear Air Turbulence,” filed Jul. 6, 1998,and Ser. No. 60/097,536 having the same title filed Aug. 21, 1998 eachof which is incorporated herein by reference.

BACKGROUND OF THE INVENTION

This invention relates to the detection of clear air turbulence,vertical windshear and wake vortices; and more particularly, to systemsfor alerting pilots to the presence of these hazards.

Clear air turbulence (CAT) and wake vortices present potential hazardsto aircraft in flight. An aircraft passing through such phenomenon mayexperience an upset from steady, equilibrium flight. This upset may besevere enough to cause injury to passengers or in severe cases may causea departure from controlled flight. CAT is a weather phenomenon that isdue to vertical wind shear in the atmosphere and usually occurs intemperature inversion layers typically found in the tropopause.

Since the conditions that result in clear air turbulence are notvisually apparent nor are they generally detectable by active sensorssuch as radar, there have been a number of attempts to detect wind shearand clear air turbulence conditions by passive detectors. In particular,attempts have been made to sense air temperature gradients, which areassociated with air turbulence, by detecting the radiation emanatingfrom the atmosphere ahead of the aircraft in the infrared and microwavespectral regions. The intensity of the detected radiation varies withthe atmospheric temperatures along the line of sight of the detector.Typically these passive systems use a radiometer to measure the thermalradiation from one of the atmospheric gases such as carbon dioxide(CO2), oxygen (O2) or water vapor (H2O) to determine changes in thespatial temperature profile in front of the aircraft. Examples of suchapproaches based on the infrared emission of CO2 are provided in U.S.Pat. Nos. 3,475,963, 3,735,136, 3,780,293, 3,935,460, 4,266,130,4,427,306, 4,937,447, 4,965,572, 4,965,573, 5,105,191, 5,276,326 and5,285,070. Other approaches determine atmospheric temperature bymeasuring the microwave emission from O2 as described in U.S. Pat. Nos.3,359,557, 3,380,055, 4,346,595, and 5,117,689.

Systems for measuring atmospheric temperature based on infrared emissionfrom H2O are described in U.S. Pat. No. 4,266,130 and in the paper byKuhn et al, “Clear Air Turbulence: Detection by Infrared Observations ofWater Vapor” in Science, Vol. 196, p.1099, (1977). In addition, therehave been several papers written describing these types of passiveinfrared systems including: S. M. Norman and N. H. Macoy, “RemoteDetection of Clear Air Turbulence by Means of an Airborne InfraredSystem,” AIAA Paper No. 65-459 presented at the AIAA Second AnnualMeeting, San Francisco, Calif., Jul. 26-29, 1965; and R. W. Astheimer,“The Remote Detection of Clear Air Turbulence by Infrared Radiation” inApplied Optics Vol. 9, No. 8, p.1789 (1970). In U.S. Pat. No. 4,346,595,Gary describes a microwave radiometer for determining air temperaturesin the atmosphere at ranges of about 3 km from the aircraft for thepurpose of detecting the height of the tropopause and the presence oftemperature inversions. He teaches that by flying the aircraft above orbelow the tropopause or temperature inversion layer, it is possible toavoid CAT. Since the effective range of the microwave radiometer isrelatively short, the system doesn't provide sufficient warning time forthe aircraft to avoid the CAT condition. The present invention hasdetection ranges on the order of 100 km which will allow time for theaircraft to change altitude to avoid CAT.

A number of the above systems were not successful or were only partiallysuccessful because they were based solely on the measurement ofatmospheric temperature in order to predict the presence of turbulence.A more reliable indication of atmospheric turbulence can be realized bydetermining the Richardson number, Ri. The use of the Richardson numberto determine the stability of the atmosphere is well known inmeteorology (see, for example, D. Djuric, “Weather Analysis,” PrenticeHall, Englewood Cliffs, N.J., 1994, p. 64). In U.S. Pat. No. 5,117,689,Gary discussed the correlation of the reciprocal of the Richardsonnumber with the occurrence of CAT conditions. The Richardson number, Ri,contains two components: (1) the vertical lapse rate of potentialtemperature and (2) the wind shear which is related to the horizontaltemperature gradient. A number of the prior art discussions measure thevertical temperature lapse rate. Gary used the inertial navigationsystem (INS) to measure the East-West and North-South components of thewind (the wind shear) along with a microwave radiometer to measure theair temperature vertical lapse rate. This information is then used tocalculate the Richardson number or its reciprocal. The deficiency of thesystem described in this patent (U.S. Pat. No. 5,117,689) is that itdetermines the Richardson number at relatively close ranges (less than 3km) and therefore does not provide advance warning of the CAT conditionand that it measures the wind shear only at the aircraft.

Previous approaches for the determination of the range and probabilityof CAT can be summarized as follows:

U.S. Pat. No. 5,276,326 to Philpott determines turbulence as a functionof temperature vs. range through the analysis of infrared radiometersignals at two or more discrete wavelengths. The temperature associatedwith a given range as a function of wavelength is then derived through amatrix inversion process. This transition is difficult and requiresnoise and error free input data to yield valid results. Gary overcomesthe multiple wavelength difficulty in U.S. Pat. No. 4,346,595 bymeasuring effective temperature and range at a single wavelength,however no attempt is made to determine the probability of clear airturbulence using the Richardson number (Ri). In U.S. Pat. No. 5,117,689,Gary teaches the significance of the Richardson number in CAT predictionbut does not suggest a method to derive Ri directly from radiometricmeasurements of horizontal and vertical temperature lapse rates obtainedby combining azimuth and elevation scanning with the aircraft motion toproduce a temperature map.

The above methods for airborne detection of clear air turbulence requirethe use of an aircraft sensor. Both infrared and radar sensors have beensuggested for use. The practical difficulties involved with implementingthese systems are several. First, the extremely small changes intemperature associated with the rising air current must be detected bythose systems using infrared sensing. This task can be difficult toaccomplish in thermally noisy environments or at long range. Second,such infrared systems require a clear lens to protect the infraredsensor. Real world flight conditions make the protection and maintenanceof the lens such that reliable readings could be had costly anddifficult. Third, those systems employing radar must have either adedicated radar or must employ existing aircraft radars originallydesigned and dedicated for other purposes. Dedicated radar systems, suchas LIDAR, tend to be extremely heavy which imposes fuel and capacitycosts on the aircraft operator. The operator also must shoulder theadditional burden of acquiring and maintaining a separate radar system.Fourth, the sensor is required to sweep out a large expanse of area into either side of the aircraft and at various ranges in front of theaircraft. This requirement means that the sensor and the associatedsignal processing system must acquire and analyze a large quantity ofdata. Detecting the subtle changes indicative of turbulence becomes moredifficult at long range. Furthermore, the bandwidth and time dedicatedto the sensing activity can become onerous when the sensor is sharedwith other tasks, or when rapid update rates are desired.

Other solutions for avoiding invisible flight hazards such as CATinvolve the use of mathematical atmospheric models. In particular, wakevortices models have been promulgated for several aircraft types. Airtraffic controllers in the United States employ these models to developseparation rules such that one aircraft's vortices do not pose a hazardto others. One such model used by controllers is called AVOSS, orAircraft Vortex Separation System. Such models do not actually detectthe presence of vortices or turbulence, but merely indicated theoreticalbehaviors and regions of likely occurrence.

SUMMARY OF THE INVENTION

The present invention recognizes the advantages of providing pilots witha means for alerting of the possibility of clear air turbulence orhazardous wake vortices. The present invention provides the pilot withtactical information such that the pilot may divert or take othercorrective action. The present invention may be utilized to warn ofthese hazards both proximate and at an extended range from the aircraft.

In recent years, it has been determined that various meteorologicalmodels can reconstruct and predict severe weather phenomena, givenadequate sounding data as initial and boundary conditions. With therapid advancement of computer processing, these models can now run onhigh-end personal computers for small spatial and temporal scales.Furthermore, the possibility of using a high-speed avionics data link toprovide sounding data, not available before, offers the possibility ofnew approaches to the CAT problem.

Thus, according to one aspect of the invention, ground based uplinkedweather information and local information generated by sensors on-boardthe aircraft are used to model clear air turbulence in the flight pathof the aircraft.

According to a further aspect of the invention, a nested grid modelingalgorithm is utilized to process the coarse-modeling and observationalinformation. The coarse-modeling information is used to modellarge-scale weather conditions in a large grid including the flight pathof the aircraft. Observational information refines the weatherinformation in a smaller grid, nested in the larger grid, that includesthe flight path of the aircraft. The refined information is utilized topredict CAT in path of the aircraft and provide a nowcast alerting thepilot of CAT.

According to another aspect of the invention, the coarse modelinginformation can be pre-stored on-board the aircraft or uplinked using adata link on the aircraft.

According to another aspect of the invention, a CAT nowcast systemincludes an on-board computer, on-board sensors, on-board storage and adata link. The on-board computer processes coarse simulation data andobservational data, either generated by the on-board sensors or uplinkedvia the data link, to nowcast CAT along the flight path. On boardinstrumentation is coupled to the on-board computer to alert the pilotof CAT.

According to another aspect of the invention, the on-board sensors, datalink, and instrumentation are existing equipment on the aircraft usedfor other purposes as well as CAT nowcasting.

According to another aspect of the invention, the coarse modelinginformation includes turbulence forecasts. Observational information isused to refine the turbulence forecast to provide a turbulence nowcastto alert the pilot of CAT occurring along the flight path of theaircraft.

According to another aspect of the invention, an infrared radiometer,which detects temperature gradients, is used as an on-board sensor todetect CAT.

The present invention has the additional advantage of making maximum useof the value of existing aircraft instruments, such as weather radar andEGPWS, to provide observational information.

According to another aspect of the present invention, a system isprovided in which a mathematical model and/or atmospheric data isuplinked to an aircraft. The uplinked data contains information onpossible vortex characteristics and/or weather phenomenon. Thisinformation is combined or utilized on board the aircraft to develop areal time airborne model of where these hazardous phenomenon are likelyto be encountered. The predictive model can be used to assert an auraland/or visual warning to the pilot.

According to one aspect of the present invention, this predictive modelis combined with detection. The predictive model is employed by theinvention to direct the sensor system to scan those areas of interest.Thus, the present invention has the advantage of providing faster updaterates than would be available in a prior art system. The presentinvention has the further advantage of minimizing the number of radarscans that must be dedicated to this task when the radar or sensor isshared amongst various data gathering functions.

According to yet another aspect of the present invention, the systemadditionally receives updated enroute weather information.

According to still another aspect of the present invention, the presentinvention receives uplinked data from ground based radar systems. Theinformation uplinked to the airborne detection system assists thatsystem in defining the particular indicia of the turbulence hazard. Thisinformation enables the present invention to better discriminate amongstthe sensor data and improves the reliability that a hazard will bedetected. In addition, this information reduces the chances that a falsewarning will be output to the pilot. As is well known to those of skillin the art, frequent false, or nuisance, warnings cause the cockpit crewto ignore subsequent and possibly valid warnings. Therefore, it isdesirable to reduce the number of false alerts in the manner taught bythe present invention.

According to an additional aspect of the present invention, theinvention contains a database of terrain information. Optionally, thisterrain data may also be uplinked to the aircraft via a communicationslink or may be contained in an existing aircraft system, such as, forexample, an Enhanced Ground Proximity Warning System (EGPWS) or anavigation database. Terrain data may also be acquired via terrain datascans of the on board weather radar. The terrain data may be used by thepredictive modeling system of the present invention to identify areas ofpossible turbulence hazards, e.g. mountain waves, or to assist inmodeling the propagation of wake vortices and dissipation of turbulence.Such information would be particularly useful in the vicinity ofairports during the landing and takeoff phases of flight.

Data uplinked to the aircraft may be uplinked via satellitetelecommunications systems as known to those of skill in the art. Thedata uplink may also occur via known and existing on boardtelecommunications devices such as ACARS or HF radio communicationslinks. Optionally, the present invention may include its own dedicatedhardware for receiving these information updates.

Warnings provided to the pilot may include an aural and/or visualwarning.

In one embodiment, externally generated turbulence forecast informationis provided to the on-board system. The system utilizes observationaldata to refine the provided turbulence forecast information to provide anowcast of expected CAT along the flight path of the aircraft.

Other features and advantages will be apparent in view of the followingdetailed description and appended drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a conceptual diagram of a model-based airborne CATnowcast/avoidance system;

FIG. 1B is a conceptual diagram of an example system for implementingthe invention;

FIG. 1C is a flow chart depicting the steps of a first embodiment of theinvention;

FIG. 1D is a flow chart depicting the steps of a second embodiment ofthe invention;

FIG. 1E is a block diagram of a preferred embodiment;

FIG. 2A is a functional block diagram of a CAT sensing system accordingto an embodiment of the invention;

FIG. 2B is pictorial representation of a scanning array illustrating theoperation of a radiometer in the invention of FIG. 2A at three timeintervals according to an embodiment of the present invention;

FIG. 2C is a pictorial representation of a section of the atmosphereillustrating the operation of the radiometer of FIG. 2A according to anembodiment of the present invention;

FIG. 2D is a pictorial representation of an aircraft operating theradiometer of FIG. 1 in a horizontal scan mode according to anembodiment of the present invention;

FIG. 2E is a pictorial representation of an aircraft acquiring ahorizontal temperature map according to the invention of FIG. 2A;

FIG. 2F is a pictorial representation of an aircraft operating theradiometer of FIG. 1 in a vertical scan mode according to an embodimentof the present invention; and

FIG. 2G is a pictorial representation of the determination of thedirection and velocity of wind at a level above the flight level of theaircraft according to an embodiment of the present invention.

FIG. 3A shows tilt angle as a function of altitude for take-off andlanding;

FIG. 3B is a flow chart of a tilt angle schedule;

FIG. 4A illustrates a weather uplink and display architecture accordingto one embodiment of the present invention;

FIG. 4B illustrates a typical cockpit display installation according toone embodiment of the present invention;

FIGS. 4C and 4D show examples of weather polygons according to oneembodiment of the present invention;

FIG. 4E illustrates a weather product; and

FIG. 4F illustrates another weather product, including an example of aweather polygon according to one embodiment of the present invention.

DESCRIPTION OF THE SPECIFIC EMBODIMENTS

Airborne Sensor Detection

FIG. 1A is a conceptual diagram of a model-based airborne CATnowcast/avoidance system. Inputs to the model are from data link and/orfrom on-board sensors.

FIG. 1A illustrates one embodiment of a model-based airborne CATnowcast/avoidance system. A data link provides large-scale weatherinformation from ground stations and environmental data from otherairplanes. An airborne system combines the information from the datalink with on-board sensors to enable CAT nowcast for an area about 100km ahead. This will give pilots about 10 minutes of warning time. Theproposed system overcomes the difficulties associated with a purelyground-based uplinking system. Such a system requires a largecommunication bandwidth and makes the airplane dependent on groundstations and a communication link with the ground. An airborne systemcombined with selective data-linked inputs will decrease such risk andgives more control to the pilot.

The detection of CAT is a difficult problem. CAT generally occurs as oneof four types: turbulence near thunderstorm (TNT), mountain waveturbulence (MWT), clear-air turbulence in the free atmosphere withoutany visible activity (CAT), and low-level turbulence (LLT). TNTconstitutes a large amount of information, the nowcast on TNT requiresless real-time computation and does not depend as much on data linkinformation. The algorithms and methodologies developed for TNT and MWTnowcast can be expanded and applied for CAT warning.

Using data from ground and airborne radar, a small-scale model cansimulate weather development with sufficient accuracy for TNT nowcast.Given the limited computational capacity on the airplane, a model aimedat a small area along the flight path can be developed by modifyingexisting large-scale meteorological models. This airborne modelingsystem takes advantage of all the information it can get from aground-based system (such as large-scale weather information andmodeling results) and reduces the computation complexity by narrowingthe field of regard for the on-board modeling and prediction algorithm.

Most existing models are for meteorological research and forecast withlarge spatial and temporal scale and also stimulate many meteorologicalparameters not of interest here. An embodiment of the present inventioncan employ a simplified model to establish an airborne model running ona personal computer that gives information for limited spatial andtemporal bounds: about 100 km along the flight path and 10 minutes ofwarning time to the pilots. A nested-grid modeling approach is used in apreferred embodiment. Most ground-based systems provide 36-km to 12-kmregional weather forecast every hour. The result can be used to provideinitial and boundary conditions for further air-borne finer-gridmodeling. The radar data can be used to correct the coarse-grid modelingresult. For example, inaccurate position and speed of a convectivesupercell forecasted by a ground-based system can be corrected by radardata and more accurate initial and boundary conditions can be formed forfurther airborne small-scale modeling.

FIG. 1B is a more detailed depiction of a preferred embodiment of theinvention. Coarse resolution forecasts for large grids, e.g., 4,000 by500 km are received periodically from land-based weather stations.Own-aircraft observational data such as Radar, Lidar (light detectionand ranging), and infrared (IR) as well as datalinked data such as datalinked from satellites, other aircraft, or ground stations is updatedabout every 10 minutes and used to model a nested grid of about 200 by50 km which is oriented to include the path of the aircraft. The fineresolution modeling data is processed by a nowcast algorithm todetermine if CAT is likely to occur in the path of the aircraft.

Several existing models known to those of skill in the art may bemodified as described above for use in the present invention. They areNASA's terminal area simulation system (TASS), see, e.g., F. H. Proctor,The Terminal Area Simulation System, NASA Contract Report 4046, 1987,and integrated electromagnetic sensor simulation (IESS),PennState/NCAR's meso-scale model 5 (MM5), see. e.g., Phillip L.Haagenson et al, The Penn State/NCAR Mesoscale Model (MM5) Source CodeDocumentation, March 1994, the Advanced Regional Prediction System(ARPS), see, e.g., Ming Xue et al., “ARPS Version 4.0 User's Guide,”Center for Analysis and Prediction of Storms (CAPS), University ofOklahoma, Norman Okla., 1995.

The uplinked data transmitted to the aircraft from ground stationscontains information on possible vortex characteristics and/or weatherphenomenon. The ground based radar systems may include weather, wakevortices and/or turbulence detection information.

In a preferred embodiment of the invention, this information is combinedor utilized on board the aircraft to develop a real time airborne modelof where these hazardous phenomenon are likely to be encountered. Thepredictive model can be used to assert an aural and/or visual warning tothe pilot.

In a preferred embodiment, this predictive model is combined withdetection. The predictive model is employed by the invention to directthe sensor system to scan those areas of interest. Thus, the presentinvention has the advantage of providing faster update rates than wouldbe available in a prior art system. The present invention has thefurther advantage of minimizing the number of radar scans that must bededicated to this task when the radar or sensor is shared amongstvarious data gathering functions.

The information uplinked to the airborne detection system assists thatsystem in defining the particular indicia of the turbulence hazard. Thisinformation enables the present invention to better discriminate amongstthe sensor data and improves the reliability that a hazard will bedetected. In addition, this information reduces the chances that a falsewarning will be output to the pilot. As is well known to those of skillin the art, frequent false, or nuisance, warnings cause the cockpit crewto ignore subsequent and possibly valid warnings. Therefore, it isdesirable to reduce the number of false alerts in the manner taught bythe present invention.

In one embodiment, the invention contains a database of terraininformation. Optionally, this terrain data may also be uplinked to theaircraft via a communications link or may be contained in an existingaircraft system, such as, for example, on Enhanced Ground ProximityWarning System (EGPWS) or a navigation database. Terrain data may alsobe acquired via terrain data scans of the on board weather radar. Theterrain data may be used by the predictive modeling system of thepresent invention to identify areas of possible turbulence hazards or toassist in modeling the propagation of wake vortices and dissipation ofturbulence. Such information would be particularly useful in thevicinity of airports during the landing and takeoff phases of flight.

Data uplinked to the aircraft may be uplinked via satellitetelecommunications systems as known to those of skill in the art. Thedata uplink may also occur via known and existing on boardtelecommunications devices such as ACARS or HF radio communicationslinks. Optionally, the present invention may include its own dedicatedhardware for receiving these information updates.

Warnings provided to the pilot may include an aural and/or visualwarning. In one embodiment, the visual warning includes icons thatsymbolize various types of weather phenomenon including clear airturbulence and vortices. In another embodiment of the present inventionthe visual display includes icons overlayed on top of the weather radarpicture.

Alternative preferred embodiments of a computational method are depictedin FIGS. 1C and 1D. Referring first to FIG. 1C, coarse resolutionsimulation data and observational data are provided to the on-boardcomputer which then performs a nested fine-resolution simulation ofatmospheric conditions along the aircraft flight path. This fineresolution data provides the parameters to perform a turbulence indexcalculation which is the basis of a “nowcast” provided to the aircraftcrew updating them on the possibility of encountering CAT. The coarseresolution data provides a “forecast” of weather events over a longperiod, e.g., 24 hours, whereas a “nowcast” provides much more accuratepredictions of weather phenomena in the very near future, e.g., 10 to 30minutes. The various functions performed will now be described.

Coarse resolution simulation data may be provided to the aircraft eitherthrough a datalink or be pre-loaded into the aircraft prior to take-off.A “snapshot” of data could be stored in no more than 6 MB in compressedform and could include data covering, for example, an area of 4,000 by500 km with 36-km horizontal resolution and 20 layers of verticalresolution. A snapshot data includes all the simulation parameters foreach point in 3-D grid space. If the computer is to be pre-loaded withhourly forecast data for 10 hours of flight time, the total amount ofdata would be about 60 Mb. Forecast data from the National Center forEnvironmental Prediction (NCEP) is readily available for this purpose.

During flight, observation data will be gathered to the airbornecomputer. These data could be gathered by detectors such as radar,lidar, infrared remote sensors, and other temperature and wind sensors.The data could also be gathered by sensors from satellites. Thedetectors could either be located on the aircraft, on other aircraftnear the flight path, ground stations, or on satellites. A data link isused to transmit data from locations not on the aircraft to theaircraft. Data conditioning and interpolation will be applied toeliminate bad data points and to fill in empty points. Meteorologicaldata variables are computed from these data to be used for fine-nestedgrid simulation.

The observational data and coarse-resolution data are used for nestedfine-resolution simulation. The coarse resolution data, e.g., forecastdata from NCEP, is used to initialize the coarse grid and establishboundary conditions and initial parameters for modeling fine grids,nested within the coarse grids, to improve the data. Mathematicalsystems for performing nested grid modeling include the Advance RegionalPrediction System (ARPS), Xue et al., “ARPS User's Guide Version 4.0,”Center for Analysis and Prediction of Storms (CAPS), 1995 and NCAR'SClark-Hall Code Model, Clark et al., “Source Code Documentation for theClark-Hall Cloud-Scale Model Code Version G3CH01,” NCAR, Boulder, Colo.,1996.

The meteorological variables calculated by the nested grid simulationare utilized to calculate the turbulence index. Particular variablesused include turbulence kinetic energy (TKE), Richardson's number (seebelow), vertical windshear, the deformation index, eddy dissipationrate, TI2, etc. The turbulence index is defined as the weighted andnormalized summation of various combinations of the these parameters.Weighting factors are assigned by using experience formulae, which aredeveloped by comparing the numbers against available flight data withreal turbulence encounters. The values depend on the location of theaircraft (mountainous or flat terrain), seasons, and other parameters.

The nowcast is based on the value of the calculated turbulence index. Ifthe calculated turbulence index for a location along the flight pathexceeds a pre-defined turbulence threshold then a turbulence warningwill be issued for its location, time, and intensity.

Referring now to FIG. 1D, this method requires less computational powerfrom the aircraft computer. As in the method of FIG. 1C, coarseresolution simulation and observational data is provided. In this case aturbulence forecast is also provided. The onboard computer utilizes theobservational information to correct the forecast to generate a nowcast.

Many agencies and service centers issue aviation turbulence forecastsbased on coarse-resolution modeling results. The accuracy may be poordue to the nature of the forecast, i.e., relative long time span, lowresolution, and local weather phenomena not included in simulation.However, the forecast result can be used together with observationaldata to improve its accuracy and give a good nowcast product.

The accuracy of the coarse-resolution turbulence forecast can beimproved by comparing observational data with coarse-resolution databecause errors in the forecast can be corrected by results of localizedobservations. For example, the forecast may predict turbulence inlocation (x,y) at time t, with associated wind and temperature profilesin an area A. However, the observational data may indicate similar windand temperature profiles but in a different area B. This difference maybe caused by inaccuracies in coarse-resolution simulation. By comparingthe two sets of data, the airborne computer may issue a turbulencewarning at a shifted location from area A. Another example is when thecoarse-resolution data and observational data have overlappingmeteorological profiles, but with different intensities. This will leadto turbulence nowcast with increased or decreased severity thanpreviously forecast.

An on-board system for providing a CAT nowcast is depicted in FIG. 1E.An on-board computer (OBC) 1 executes software that implements thenested grid algorithm and CAT nowcast as described above. This nowcastinformation is provided to cockpit instrumentation 2 which providesaural or visual CAT nowcast alerts to a pilot. On board storage 3 isused to store pre-loaded coarse simulation data, terrain databaseinformation, and program code. On board sensors 4 and a data-link 5provide observational data to the OBC 1. Further, the data-link can beused to provide coarse simulation data or program code to be stored inthe on-board storage. All or some of the elements of the system depictedin FIG. 1E may be located on-board the aircraft.

FIG. 2A provides an overview, in the form of a functional block diagram,of the operation of an airborne sensing device 10 for installation in anaircraft to detect wind vector difference and clear air turbulence.

As described above, the information generated by the airborne sensingdevice 10 may be utilized as observational data to refine coarsesimulation data in the nested grid approach or to refine CAT predictiondata. Alternatively, the sensor data may be independently processed topredict the occurrence of CAT along the flight path of the aircraft.

Installed in a forward and partially sideways-looking location of theaircraft, such as the nose or a leading portion of a wing, is a passivedetector 12, preferably a radiometer, for receiving infrared radiationfrom the atmosphere as indicated by a dashed line 14. Also, as indicatedby a block 16, the radiometer 12 is connected to a directional scanningmechanism which permits the radiometer 12 to receive the radiation 14from different directions in both the azimuth and vertical directions orin only the azimuth direction.

Shown at block 18, the apparatus 10 converts the sterance or energy L ata particular wave length λ of the radiation 14 as detected by theradiometer 12 into a value T_(eff) which represents the temperature ofthe atmosphere at an effective range R_(eff) from the aircraft. Theconcept of converting the radiation 14 into temperature T_(eff) and theeffective range R_(eff) will be described below.

Then, as indicated at a block 20, the T_(eff) values obtained will beused to create a horizontal or vertical temperature map of atmospherictemperature ahead of the aircraft as illustrated in FIGS. 2B-2G. As theaircraft progresses along its line of flight, the system data iscollected as shown in FIG. 2B. The apparatus then generates atemperature map as indicated at 20.

The temperature mapping 20 is used to compute horizontal temperaturegradients {overscore (V)}T, indicated at a block 22, between thetemperatures T, contained in the map 20 in a horizontal plane.

As represented by a block 24 and discussed below, the horizontaltemperature gradients {overscore (V)}T can be used to compute verticalwind vector difference for flight levels ahead as well as above andbelow the aircraft.

Effective use of the wind vector difference information generated at 24can be made, as shown at a block 26, by displaying the wind vectordifference at flight levels above or below the aircraft in order toprovide the air crew with information as to winds that might be morefavorable. This information 24 can also be used as an input to a flightmanagement system, indicated by a block 28, so that it can be combinedwith other flight parameters to provide guidance as to the mostefficient flight regime. In addition, this information 24 can be used tocompute the probability of clear air turbulence, as indicated by a block30 that in turn can be used as an input to a clear air turbulencedisplay or warning system as shown by a block 32.

The following is a more detailed description of the various elements andconcepts of the invention as shown in the block diagram of FIG. 2A.

For example, FIG. 2B provides an illustration of the operation of theradiometer 12 in conjunction with the directional scan mechanism 16. Inthis case the scan mechanism 16 directs the radiometer 12 so as toreceive radiation 14 from what in effect are 3×3 arrays 34 a, 34 b and34 c of points in the atmosphere ahead of the aircraft collectingsterance associated with an effective range R_(eff) at time intervalst₀, t₁, and t₂. In the preferred embodiment of the invention, a middlerow 36 of the arrays 34 a-c is located at the aircraft's flight levelwhile an upper row 38 is located at a level intermediate between theflight level and an upper flight level and a lower row 40 is located ata level intermediate between the flight level and a lower flight level.An illustration of the flight levels is provided in FIG. 2G. Theradiometer 12 can be any suitable commercially available radiometer or aradiometer of the type described in the above referenced patents such asU.S. Pat. No. 4,937,447 to Barrett, which is hereby incorporated byreference. In another preferred embodiment, only one horizontaltemperature map at one level is used for determining wind difference.

Referring also to FIG. 2A and FIG. 2C, the temperature conversion 18 ofeach point in the arrays 34 a-c is accomplished by translating theradiance L(λ) received by the radiometer 12, where the wavelength is λ,into a signal that is associated with a temperature T_(eff) of thevolume of air seen by the radiometer. The temperature, T_(eff), isassociated with the effective range, R_(eff). which is the weightedaverage distance of the signal reaching the radiometer 12. This use ofR_(eff) is only useful in conditions for which R_(eff) does not varysignificantly during aircraft flight across reasonable distances at afixed altitude. It has been found that R_(eff) does not varysignificantly for normal flight conditions, i.e., R_(eff) is determinedby only the wavelength λ, the altitude and latitude of the aircraft andthe particular time of year. This has been verified through the use ofthe FASCODE program. The FASCODE program is a computer model ofatmospheric transmission and radiance in the infrared. This program isdescribed and identified in the aforementioned Barrett, U.S. Pat. No.4,937,447. The following Table 1 is a table illustrating the FASCODE(using the mid-latitude, winter atmosphere program) computed effectiverange R_(eff) vs. λ in the case that λ falls within the preferred bandof wavelengths of CO₂ emission for a zenith angle of 90 degrees and analtitude of 35,000 ft.

TABLE 1 Wavelength (μm) Effective Range (km) 12.2 121 12.3 106 12.4 98.212.5 84.4 12.6 76.6 12.7 91.8 12.8 105 12.9 106 13.0 89.3

It has been found that the wavelength 12.2 μm of CO₂ is particularlyeffective at measuring T_(eff) associated with a range R_(eff) ofapproximately 120 km for one altitude and latitude. It should be notedthat one of the advantages of the invention is that it makes use ofpreviously computed values of R_(eff) so that it is possible to provideaccurate maps of atmospheric temperature. Also it is possible to storetables of R_(eff) vs. Altitude and λ vs. R_(eff) such as shown in theTable 1 above in order to adjust the sensitivity of the system and theeffective range for various conditions. Alternatively, it is possible touse more than one wavelength λ to measure more than one T_(eff) atcorresponding ranges R_(eff) from the aircraft.

The radiance L(λ) detected by the radiometer 12 is a function of thetemperature of the naturally occurring CO₂ in the atmosphere. It ispossible to associate the temperature of the air in ΔV_(vol) shown inFIG. 2C with a given signal. The total signal, L(λ), is the sum of thecontributions, L(λ)_(i) of signal from each volume element i along theline of sight of the radiometer 12. $\begin{matrix}{{{Thus}\quad {L(\lambda)}} = {{\sum\limits_{i}{L(\lambda)}_{i}} = {\sum\limits_{i}{S_{i}\tau_{i}}}}} & (1)\end{matrix}$

where S_(i) is the radiance intercepted by the detector from a volumeelement i and τ₁ is the transmission of the radiance between the volumeelement i and the detector. The temperature T_(eff) is associated withL(λ), where T_(eff) is the temperature of a blackbody source whichproduces the same radiometer signal as L(λ). The effective distanceR_(eff) is defined according to the equation $\begin{matrix}{R_{eff} = \frac{\sum\limits_{i}{R_{i}{L(\lambda)}_{i}}}{\sum\limits_{i}{L(\lambda)}_{i}}} & (2)\end{matrix}$

indicated at 18 of FIG. 2A, the temperature T_(eff) is associated withR_(eff) and a map is generated at 20 with the temperature T_(eff) at adistance R_(eff) in the appropriate direction from the aircraft. Fornormal flight conditions, R_(eff) does not vary significantly and isdetermined only by altitude and latitude for a given time of year. Withrespect to FIG. 2C, the altitude of ΔV_(vol) for a R_(eff) of 120 kmwill be about 1000 ft. above the flight level of the aircraft due to theearth's curvature assuming the radiometer 12 is directed toward thehorizon.

FIGS. 2D-2F illustrate how the temperature mapping 20 can beaccomplished. In FIG. 2D, an aircraft 42 having the radiometer 12mounted in its nose causes the radiometer 12 to perform an azimuth scanof 180°. At each of the five positions shown in FIG. 2D, the radiometer12 will detect the radiance 14. In this manner a horizontal temperaturemap is generated. The radiometer can detect signals sufficiently fastthat the motion of the aircraft can be ignored. FIG. 2E shows a seriesof locations indicated by a set of rectangular boxes 44 _(a-d) thatcorrespond to a set of time intervals t_(a-d) as the aircraft 42proceeds along its flight path, where the temperatures T_(eff) detectedfor each location 44 _(a-d) can be stored in memory. Similarly, asillustrated in FIG. 2F, the radiometer 12 in the aircraft 42 can performa vertical scan so that temperatures of locations above and below theflight path can be mapped. As a result, it is possible to generatetemperature maps for horizontal planes above and below the aircraft 42.

By mapping the temperature fields 20 as described above, it is possibleto compute horizontal temperature gradients {overscore (V)}T asindicated at 22 of FIG. 2A. It is also possible, by using the verticaltemperature mapping to calculate the temperature lapse rate ∂T/∂z foruse in calculation of the Richardson Number for computing theprobability of clear air turbulence.

As is illustrated by the representation of FIG. 2G, one of the salientfeatures of the invention is the capability of utilizing the temperaturegradients computed at 22 to generate values representing vertical windvector difference or horizontal winds at various flight levels. In thiscase, only a horizontal mapping at one level is needed. For example, amethod according to the invention whereby the thermal wind concepts canbe used to compute vertical wind vector difference, ΔV, as indicated at24 of FIG. 2A, makes use of the following relation: $\begin{matrix}{{\Delta \quad V} = {{- \left\lbrack \frac{g\quad \Delta \quad z}{fT} \right\rbrack}{{\nabla\quad T} \otimes k}}} & (3)\end{matrix}$

where g is the acceleration due to gravity, Δz is the distance betweenZ₁ and Z₂, f is the Coriolis parameter resulting from the earth'srotation, T is the temperature at said flight altitude Z₁, {overscore(T)} is the vector representing the temperature gradient at theintermediate level Z₃ between Z₁ and Z₂, k is the unit vector parallelto the aircraft's local vertical and the symbol {circle around (X)}represents the vector cross-product operator. In FIG. 2G, Z₁ denotes thecurrent flight level of the aircraft, Z₂ denotes the flight level abovethe aircraft and Z₃ denotes the intermediate level. Equation 3 may befound in any standard meteorological text such as “Dynamical andPhysical Meteorology,” by G. J. Haltiner and F. L. Martin, (McGraw-Hill,New York, 1957) p. 204.

As a result, once the temperature gradients are computed 22 from thetemperature field 20 the value of ΔV can be computed at 24 for the upperflight level 48 per equation (3). For an aircraft direction vector,V_(ac), the vector dot product, ΔV•V_(ac), is the increase in headwindor tailwind the aircraft would experience at the different altitude. Inaddition, the vector value ΔV can then be added to the vector value V₁of the wind at the current flight level 46 to obtain a vector value V₂which represents the direction and speed of the wind at the upper flightlevel 48. This value then can also be displayed on the display 26 inorder to provide the air crew with information as to the wind at theupper flight level 48. Alternatively, the display 26 can be used todisplay just the difference in wind speed along the direction of theaircraft's flight at the upper flight level 48, for example bydisplaying a simple plus or minus sign along with a value representingthe difference in velocity. In addition, the value of V₂ can be used asan input to the flight management system 28 so that factor can be usedby the system 28 in determining the most efficient flight regime. Notethat the temperatures are only needed in one horizontal plane todetermine {overscore (T)}, and the wind difference, ΔV.

It will be understood that the above discussed method of determiningwind direction and velocity V₂ at the upper flight level 48 would alsoapply to the determination of wind at a lower flight level below thecurrent flight level 46. In this manner, it is possible to provide onthe display 26 or to the flight management system 28 an indication ofthe winds both above and below the aircraft so that the crew can takeadvantage of this information in selecting the most fuel efficientaltitude.

Another feature of the invention relates to the use of the temperaturemapping function 20 along with the computation of vertical temperaturegradients 22 to compute the probability of clear air turbulence 30. Inparticular, the vertical temperature mapping 20 can be used to calculatethe lapse rate ∂T/∂z for determination of the Richardson number Ri whichis correlated with turbulent conditions. In this case Ri is computedusing the following relations: $\begin{matrix}{{Ri} = {\left( \frac{g}{\theta} \right)\frac{\left( \frac{\partial\theta}{\partial z} \right)}{{\frac{\partial V}{\partial z}}^{2}}}} & (4)\end{matrix}$

where $\begin{matrix}{\theta = {T\left\{ \frac{1000}{p} \right\}^{\frac{R}{C_{p}}}}} & (5)\end{matrix}$

and where θ is the potential temperature, ∂θ/∂z is the vertical gradientof the potential temperature, ∂V/∂z is the vertical wind shear, g isacceleration due to gravity, V is the horizontal wind vector, z isheight, T is temperature in Kelvin, p is atmospheric pressure inmillibars, R is the universal gas constant and C_(p) is the specificheat of air at constant pressure. The Richardson number, Ri, is ameasure of the probability of CAT. For Ri below 0.21, atmosphericturbulence occurs and CAT is likely. Severity of CAT increases withdecreasing Ri. Referring again to FIG. 2A, the probability of clear airturbulence is determined at 30 with the result displayed on the CATdisplay 32.

The embodiment of the invention in FIG. 2A has been described in termsof its use in connection with an aircraft traversing temperature fieldsin its flight path. However, this type of apparatus can also adapted foruse in mapping temperature fields from a fixed geographical position. Byusing the radiometer 12 at a fixed site to scan temperature at theeffective range R_(eff) as described above over a period of time as theweather moves over the radiometer, it is possible to generate a map ofthe temperature fields for a wide area. The temperature map can then beused for warnings of wind conditions such as clear air turbulence anddry microburst conditions. Another use at a fixed position is to scanthe temperature field in 360° azimuth and in elevation to determine winddifferences, or CAT at one time.

Radar Sensing

The present invention may also incorporate the existing and/or adedicated aircraft radar sensor to scan for significant weather such asCAT ahead of the aircraft. Management of the existing weather radarscans to search for CAT type conditions are preferably interleaved withthe scans normally conducted by the weather radar during routine weatherscans. U.S. Pat. No. 5,831,570, incorporated by reference, describes onepossible interleaving technique. Other techniques are possible.

In another embodiment of the invention, the radar sensor, which may bean HF, VHF or ionosonder-like device senses atmospheric ionizationresulting from CAT and/or windshear events. Friction between moving airmasses results in ionization that causes localized changes in themaximum radio frequency that will propagate in that region. Thisproperty can be used to sense versions of clear air turbulence even indry air.

The data from the aircraft radar sensor can be utilized as observationaldata to refine coarse simulation data utilizing the nested gridalgorithm or to refine turbulence forecasts to provide a CAT nowcast.Further, coarse simulation data can be utilized to determine areas ofhigh CAT probability and to direct the radar to preferably scan thoseareas.

Tilt Control

To maximize the number and types of data scans the radar can make,automation of the radar scan or tilt controls are desirable. Thisautomation reduces pilot workload and better enables the radar toperform multiple tasks.

An automated scan management and tilt control may be provided in any oneof a number of ways. In one embodiment of the invention, the radar mayutilize a predetermined schedule of tilt angles according to heightabove ground and flight phase as depicted in FIG. 3A.

According to another embodiment of the present invention, a terraindatabase is used to automatically calculate the tilt angle. One suchdatabase is included in the Enhanced Ground Proximity Warning System(EGPWS) manufactured by Honeywell International Incorporated. Otherdatabases may be used. This embodiment of the invention utilizes theinputs described below. FIG. 3B describes a tilt angle schedule usingthese inputs to one embodiment of the invention.

Inputs

1. aircraft altitude for example, relative to sea level [alt]

2. aircraft position for example, in latitude [lat]

3. aircraft position for example, in longitude [lng]

4. terrain database [trn (ilat, ilng)] where ilat represents thelatitude index and ilng represents the longitude index

5. radar range scale in for example, nautical miles (10, 20, 40, 80,160, 320) [RS]

6. database cell size in for example, nautical miles (0.25, 0.5, 1.0,2.0, 4.0) [CS]

7. half-power elevation beam width of the weather radar for example, indegrees (i.e., the angular distance from the main antenna axis—measuredin the vertical plane containing the main antenna axis—at which thesignal strength falls to half the maximum value) [elbw]

8. aircraft heading relative to north (where positive is clockwise fromnorth) [hdg]

The schedule of FIG. 3B first determines the values of the aircraftposition variables. Then, for each latitude index within the radar rangescale and within 90 degrees of the aircraft heading, the minimum andmaximum longitude indices within those same limits are determined. Thelatitude index is then set to the minimum latitude index within therange scale and within 90 degrees of the aircraft heading and thelongitude index is set to the minimum longitude index within the rangescale and within 90 degrees of the aircraft heading and intersecting thelatitude index. A maximum angle variable (MaxAng) is created and set tonegative 90 degrees. The schedule of FIG. 3B then computes the distancebetween the aircraft and the terrain database point that corresponds tothe latitude and longitude indices.

Compensating for earth curvature and radar diffraction according totechniques known to those of skill in the art, the elevation anglebetween the aircraft and the terrain database cell (E1Ang) is measuredand compared to the maximum angle variable. If the elevation angle isgreater than the maximum angle, the maximum angle is set equal to theelevation angle. If the elevation angle is not greater than the maximumangle, the longitude index is increased by one. The longitude index isthen compared to the maximum longitude index within the range scale andwithin 90 degrees of the aircraft heading and intersecting the latitudeindex. If the longitude index is not greater than the maximum longitudeindex, then the algorithm loops back to the computation of the distancebetween the aircraft and the terrain database point that corresponds tothe latitude and longitude indices. If the longitude index is greaterthan the maximum longitude index, then the latitude index is increasedby one. The latitude index is then compared to the maximum latitudeindex within the range scale and within 90 degrees of the aircraftheading. If the latitude index is not greater than the maximum latitudeindex, then longitude index is set equal to the minimum longitude indexwithin the range scale and within 90 degrees of the aircraft heading andintersecting the latitude index and the method loops back to thecomputation of the distance between the aircraft and the terraindatabase point that corresponds to the latitude and longitude indices.If the latitude index is greater than the maximum latitude index, thenthe tilt angle is calculated by adding the maximum angle to thehalf-power elevation beam width of the weather radar.

The weather radar's antenna tilt angle maybe recomputed each time theaircraft moves outside of a database cell, changes range scale or makesa change in aircraft heading.

Weather Uplinking and Display

According to one embodiment of the present invention, the inventionincludes a display 32 (FIG. 2A) for displaying the CAT information tothe pilot. Display 32 may be a dedicated display but may also be adisplay shared with other functions, such as for example, weather radar,EFIS, FMS, EGPWS or any other aircraft display. In a preferredembodiment of the invention, a tactical display of weather data thatincludes CAT information may be displayed to the pilot. This display mayoptimally include weather and/or CAT data uplinked to the aircraft. Theexternal data source may include ACARS, HF radio linked and othersources of data linking know to those of skill in the art.

In an alternate data architecture, a first aircraft collects localatmospheric data, in situ accelerations and other flight data as afunction of aircraft position and altitude which is down-linked to aground station. The ground station may also receive weather data fromother ground based sources, satellite links, weather balloons and otherweather gathering sources known to those of skill in the art. Thedown-linked information is used to assemble weather products based on,for example, National Center of Atmospheric Research models, anddisplayed in the ground station. According to one aspect of theinvention, the invention provides multiple weather products, forexample, turbulence, position, altitude, winds, temperature, severecells from weather radar returns and other products. The ground stationup-links the weather products, for example, position, speed and track,and magnitude of significant weather to the originating aircraft andother aircraft. The weather products are received, displayed and storeduntil the next up-link is received.

The weather products up-linked, displayed and stored include, but arenot limited to, significant weather. At the pilot's discretion and fortactical use, weather areas and in particular significant hazardousweather areas are displayed on a cockpit display. According to oneembodiment of the invention, the pilot may manually select betweendisplay of the weather products information and the display of otherinformation such as, for example, terrain, weather radar or EFIS map.

FIG. 4A diagrams one possible data collection, up-link/down-link,weather product storage and display in an embodiment where aircraft alsodown-link information. In a preferred embodiment, the inventionpredominantly uses existing equipment. For example, in aircraft weatherinformation system 10 shown in FIG. 4A, an aircraft 54 collects currentlocal atmospheric data, in situ accelerations and other flight data as afunction of aircraft position and altitude using existing on-board datasources 55, for example, on-board navigation data, altitude data,atmospheric data, sensor data and weather radar return data. Theinvention stores the data in a memory storage location 56. The data isdown-linked via an antenna 58 to a ground station 60 where the data isused to assemble and refine weather products in conjunction with otheravailable weather data 61. The weather products are up-linked tooriginating aircraft 54 and other aircraft 62, 64. The weather productsare received and stored in a memory location 66 and converted to visualdepictions using a picture generator 68, for example, an existing groundproximity terrain picture and symbol generator. The video data istransmitted via the existing weather video bus interface 70 anddisplayed on one or more existing cockpit color display devices 72, forexample, an EFIS map and/or a weather radar display. Thus, it ispossible to operate independently of the aircraft system level data busand symbol generators.

In a preferred embodiment of the invention, icon images depicting andbounding significant hazardous weather are shown on existing colordisplays found in the cockpit. Each icon uniquely depicts a specificsignificant weather hazard area, for example, convective hazard areas,potential turbulence areas, winter precipitation areas or icing areas.According to one preferred embodiment of the invention, significantweather is displayed to a minimum range of 320 nautical miles along theaircraft's flight path. According to another preferred embodiment of theinvention, significant weather is displayed to a minimum range of 640nautical miles along the aircraft's flight path.

FIG. 4B illustrates a typical cockpit installation 100. The particularcockpit installation depicted in FIG. 4B is a retrofit installationwherein an aircraft instrument panel 110 includes a ground proximitywarning system accessed by weather radar/terrain switch 112. The pilot'sground proximity warning system switch panel 114 is modified toincorporate a on/off switch 116 whereby the pilot accesses thesignificant weather data upon command. Instrument panel 110 includesground proximity warning system switch panel 118.

Weather radar video data bus 70 is, for example, a video data buscompliant with Aeronautical Radio, Incorporated (ARINC) standard 453,which incorporates a limited palette of colors and has limited bandwidthcapabilities. Implementation of the invention using other video databuses is possible, however, and the invention itself is not so limited.

The icons displayed in one possible embodiment include a variety ofpolygons unique to a specific significant weather hazard, for example,convective hazard areas, potential turbulence areas, winterprecipitation areas or icing areas. In one implementation, the icons aretwo-dimensional (2D) images indicating the weather hazard's geographiclocation relative to the aircraft. According to another embodiment ofthe invention, the icons are three-dimensional (3D) images indicatingthe weather hazard's altitude relation to the aircraft in addition tothe weather hazard's relative geographic location.

FIGS. 4C and 4D show examples of weather polygons according to the. FIG.4C illustrates a cockpit display 300 selected to display data within aneighty nautical mile range of the aircraft. FIG. 4C includes an exampleof a 2D polygon-shaped image 310 depicting a predicted hazardousconvectivity activity area. According to the invention, polygon-shapedimage 310 is displayed in color, for example, polygon-shaped image 310is displayed as a red polygon shape with red color dots. According toone preferred embodiment, the weather radar returns of cells lyingwithin the hazardous convectivity activity area are displayed insidepolygon-shaped image 310.

FIG. 4D illustrates another cockpit display 400 according to oneembodiment of the invention selected to display data within a threehundred twenty nautical mile range. FIG. 4D includes an example of aunique 2D polygon-shaped image 410 depicting a predicted turbulencearea. According to the invention, polygon-shaped image 410 is displayedin color, for example, polygon-shaped image 410 is displayed as a yellowpolygon shape with yellow color dots.

On-Board Radar System and Scan Interleaving

An on-board radar system and techniques for scan interleaving suitablefor use an on-board sensor to provide observational data in thepreferred embodiments is disclosed in U.S. Pat. No. 5,831,570, assignedto the assignee of the present application, and is hereby incorporatedby reference for all purposes.

The invention has now been described with reference to the preferredembodiments. Alternatives and substitutions will be apparent to personsof skill in the art. In particular, the algorithms and services forproviding simulation data are exemplary only and not critical topracticing the invention. Alternatives will be known to persons of skillin the art and substitutes will continually be developed. Further,additional on-board sensors and off-boar sources of observational datawill continually be developed. The particular type of sensor or datasource is not critical to practicing the invention. Accordingly, it isnot intended to limit the invention except as provided by the appendedclaims.

What is claimed is:
 1. A method for detecting clear air turbulenceoccurring along the flight path of an aircraft, with the methodperformed utilizing on-board data processing equipment located on saidaircraft, said method comprising the steps of: receiving uplinkedinformation generated at ground stations providing data to be utilizedin predicting clear air turbulence; storing said uplinked information;utilizing an airborne sensor located on said aircraft to generate localinformation; storing said local information; performing a nested gridmodeling algorithm comprising the steps of: processing said uplinkedinformation to provide large scale weather modeling for a large grid,encompassing an area including the flight path of the aircraft, and toprovide initial and boundary conditions for finer-grid modeling; andprocessing said local information, said initial conditions, and saidboundary conditions to model atmospheric conditions more accuratelywithin a smaller grid, nested within said larger grid, with the smallergrid approximating the flight path of the aircraft; and predicting clearair turbulence as a function of said model of atmospheric conditions. 2.The method of claim 1 wherein said uplinked weather information includesperiodic weather forecasts for a large grid of fixed size forestablishing the initial and boundary conditions of the large grid. 3.The method of claim 1 wherein said uplinked information contains vortexcharacteristics and/or weather phenomena for the large grid.
 4. Themethod claim 1 wherein said airborne sensor is on-board weather radar,with said method further comprising: including radar data generated bythe on-board weather radar in said local information; and wherein saidstep of processing said local information further comprises the step of:correcting inaccurate predictions base on uplinked information utilizingsaid radar data and forming more accurate initial and boundaryconditions for further small scale modeling.
 5. The method of claim 1further comprising the step of: storing terrain data on said aircraftand including said terrain data in said airborne information; andprocessing said terrain information to identify areas of possibleturbulence or to assist in modeling the propagation of wake vortices anddissipation of turbulence.
 6. The method claim 1 wherein said airbornesensor is an on-board infrared radiometer to detect and quantifytemperature gradients ahead of the aircraft.
 7. A method for detectingclear air turbulence occurring along the flight path of an aircraft,with the method performed utilizing on-board data processing equipmentlocated on said aircraft, said method comprising the steps of: storingcoarse resolution simulation data aboard the aircraft; utilizing onboard sensors to generate observational information; storing saidobservational information; performing a nested grid modeling algorithmcomprising the steps of: processing said coarse simulation data toprovide large scale weather modeling for a large grid, encompassing anarea including the flight path of the aircraft, and to provide initialand boundary conditions for finer-grid modeling; processing saidobservational information, said initial conditions, and said boundaryconditions to model atmospheric conditions more accurately within asmaller grid, nested within said larger grid, with the smaller gridapproximating the flight path of the aircraft; and based on said smallergrid conditions, generating a nowcast indicating the likelihood of clearair turbulence along the flight path of the aircraft.
 8. The method ofclaim 7 further comprising the steps of: receiving uplinkedobservational information generated by devices not located on theaircraft; and where said step of processing further comprises the stepof: processing said uplinked observational information along with saidobservational information, said initial conditions, and said boundaryconditions to model atmospheric conditions more accurately within asmaller grid, nested within said larger grid, with the smaller gridapproximating the flight path of the aircraft.
 9. The method of claim 7further comprising: providing a pilot with aural or visual informationindicating the location of predicted clear air turbulence.
 10. Themethod of claim 7 where said step of storing coarse resolutionsimulation data further comprises the step of: storing terrain data; andwherein said step of processing further includes the step of: utilizingsaid terrain data to model mountain wave turbulence.
 11. The method ofclaim 7 further comprising the steps of: receiving uplinked coarsesimulation information; and wherein said step of processing furthercomprises the step of: processing said uplinked coarse simulationinformation to provide large scale weather modeling for a large grid,encompassing an area including the flight path of the aircraft, and toprovide initial and boundary conditions for finer-grid modeling.
 12. Themethod claim 7 wherein said airborne sensors include: an on-boardinfrared radiometer to detect and quantify temperature gradients aheadof the aircraft, with said method further comprising: includingradiometer data generated by the on-board infrared radiometer in saidobservational information; and wherein said step of processing saidobservational information further comprises the step of: correlatingdetected and quantified temperature gradients with turbulence events tocorrect inaccurate predictions base on uplinked information utilizingsaid radar data and forming more accurate initial and boundaryconditions for further small scale modeling.
 13. A method for detectingclear air turbulence occurring along the flight path of an aircraft,with the method performed utilizing on-board data processing equipmentlocated on said aircraft, said method comprising the steps of: storingcoarse resolution simulation data aboard the aircraft includingturbulence forecast data of clear air turbulence events; utilizing onboard sensors to generate observational information; storing saidobservational information; utilizing said observational information torefine the turbulence forecast data to more accurately predict clear airturbulence events occurring along the immediate flight path of theaircraft; and based on said refined turbulence conditions, generating anowcast indicating the likelihood of clear air turbulence along theflight path of the aircraft.
 14. The method of claim 13 furthercomprising the steps of: receiving uplinked observational informationgenerated by devices not located on the aircraft; and where said step ofprocessing further comprises the step of: utilizing said uplinkedobservational information along with said observational information torefine the turbulence forecast data to more accurately predict clear airturbulence events occurring along the immediate flight path of theaircraft.
 15. The method of claim 13 further comprising: providing apilot with aural or visual information indicating the location ofpredicted clear air turbulence.
 16. The method of claim 13 where saidstep of storing coarse resolution simulation data further comprises thestep of: storing terrain data; and wherein said step of processingfurther includes the step of: utilizing said terrain data to improveturbulence prediction accuracy.
 17. The method of claim 13 wherein saidon-board sensor is an on-board infrared radiometer to detect andquantify temperature gradients ahead of the aircraft.
 18. A systemlocated on an aircraft for nowcasting clear air turbulence eventsoccurring along the flight path of the aircraft, said system comprising:on-board storage for storing coarse simulation data, observational data,and program data, with coarse simulation data including meteorologicalforecast data for forecasting weather conditions over a large grid;on-board sensors for detecting observational information includingmeteorological data along the flight path of the aircraft; an on-boardcomputer, coupled to the on-board storage and on-board sensors toexecute program code to: process said coarse simulation data to providelarge scale weather modeling for a large grid, encompassing an areaincluding the flight path of the aircraft, and to provide initial andboundary conditions for finer-grid modeling; process said observationalinformation, said initial conditions, and said boundary conditions tomodel atmospheric conditions more accurately within a smaller grid,nested within said larger grid, with the smaller grid approximating theflight path of the aircraft, to provide a nowcast of CAT likelihoodalong the flight path of the aircraft.
 19. The system of claim 18further comprising: a means for receiving data from data sourcesexternal to the aircraft; with the onboard computer storing said data inthe on-board storage and utilizing said data as observational data. 20.The system of claim 18 further comprising: instrumentation, coupled tothe on-board computer, for providing aural or visual indications ofclear air turbulence occurring along the flight path of the aircraft.21. The system of claim 18 further comprising: a means for receivingdata from sources external to the aircraft; with the onboard computerstoring said data in the on-board storage and utilizing said data ascoarse simulation data.
 22. The system claim 18 wherein said airbornesensors include: an on-board infrared radiometer to detect and quantifytemperature gradients ahead of the aircraft.
 23. The system of claim 18wherein said airborne sensors include: on-board weather radar, with saidon-board computer executes program code to: include radar data generatedby the on-board weather radar in said observational information; andcorrect inaccurate predictions base on coarse simulation informationutilizing said radar data and forming more accurate initial and boundaryconditions for further small scale modeling.
 24. A system located on anaircraft for nowcasting clear air turbulence events occurring along theflight path of the aircraft, said system comprising: on-board storagefor storing coarse simulation data, observational data, and programdata, with coarse simulation data including turbulence forecast data forforecasting turbulence conditions over a large grid; on-board sensorsfor detecting meteorological data along the flight path of the aircraft;an on-board computer, coupled to the on-board storage and on-boardsensors to execute program code to: utilize said observationalinformation to refine the turbulence forecast data to more accuratelypredict clear air turbulence events occurring along the immediate flightpath of the aircraft; and based on said refined turbulence conditions,generate a nowcast indicating the likelihood of clear air turbulencealong the flight path of the aircraft.
 25. The system of claim 24further comprising: a means for receiving data from data sourcesexternal to the aircraft; with the onboard computer storing said data inthe on-board storage and utilizing said data as observational data. 26.The system of claim 24 further comprising: a means system for receivingdata from data sources external to the aircraft; with the onboardcomputer storing said data in the on-board storage and utilizing saiddata as coarse simulation data.
 27. The system claim 24 wherein saidairborne sensors include: an on-board infrared radiometer to detect andquantify temperature gradients ahead of the aircraft.
 28. The system ofclaim 24 wherein said airborne sensors include: on-board weather radar,with said on-board computer executes program code to: include radar datagenerated by the on-board weather radar in said observationalinformation; and utilize said radar data correct inaccurate turbulencepredictions base on coarse simulation information.
 29. A device fordetecting turbulence and for alerting the pilot of an aircraft to apotential flight hazard comprising; an input adapted to receiveatmospheric data from at least one airborne sensor; an output adapted tobe coupled to an aircraft data bus; a signal processing device, coupledto a memory device, to said input and to said output for: accessingturbulence simulation data stored in said memory device forecastprobable turbulence conditions over a large grid based on saidsimulation data; utilizing said airborne sensor to retrieve saidforecast of probable turbulence conditions to more accurately predictturbulence events over a smaller grid; and asserting a signal on saidoutput when a turbulence event is predicted in said smaller grid. 30.The device for detecting turbulence of claim 29 wherein said memorydevice includes terrain data.
 31. A device for use aboard aircraft todetect turbulence comprising: an input adapted to receive atmosphericdata from at least one airborne sensor; an output adaptive to be coupledto an aircraft data bus; and a signal processing device for: accessingturbulence simulation data stored in a memory device, forecasting areasof probable turbulence conditions based on said simulation data, andoutputting a signal to control said airborne sensor to scan said areasof probable turbulence.
 32. The device of claim 31 wherein said signalprocessing device further comprises: means for processing saidatmospheric data and outputting an alert signal when a turbulence eventis detected.